SubmissionNumber#=%=#54
FinalPaperTitle#=%=#QFNU_CS at SemEval-2024 Task 3: A Hybrid Pre-trained Model based Approach for Multimodal Emotion-Cause Pair Extraction Task
ShortPaperTitle#=%=#
NumberOfPages#=%=#5
CopyrightSigned#=%=#Zining Wang, Yanchao Zhao, Guanghui Han, Yang Song
JobTitle#==#
Organization#==#Qufu Normal University
Abstract#==#This article presents the solution of Qufu Normal University for the Multimodal Sentiment Cause Analysis competition in SemEval2024 Task 3.The competition aims to extract emotion-cause pairs from dialogues containing text, audio, and video modalities. To cope with this task, we employ a hybrid pre-train model based approach. Specifically, we first extract and fusion features from dialogues based on BERT, BiLSTM, openSMILE and  C3D. Then, we adopt BiLSTM and Transformer to extract  the candidate emotion-cause pairs. Finally, we design a filter to identify the correct emotion-cause pairs. The evaluation results show that, we achieve a weighted average F1 score of 0.1786 and an F1 score of 0.1882 on CodaLab.
Author{1}{Firstname}#=%=#Zining
Author{1}{Lastname}#=%=#Wang
Author{1}{Username}#=%=#oliver_wang
Author{1}{Email}#=%=#wzn0410@qfnu.edu.cn
Author{1}{Affiliation}#=%=#Qufu Normal University
Author{2}{Firstname}#=%=#Yanchao
Author{2}{Lastname}#=%=#Zhao
Author{2}{Email}#=%=#kang_hui1314@126.com
Author{2}{Affiliation}#=%=#Qufu Normal University
Author{3}{Firstname}#=%=#Guanghui
Author{3}{Lastname}#=%=#Han
Author{3}{Email}#=%=#hanguanghui999@gmail.com
Author{3}{Affiliation}#=%=#Qufu Normal University
Author{4}{Firstname}#=%=#Yang
Author{4}{Lastname}#=%=#Song
Author{4}{Email}#=%=#song.yang1988@163.com
Author{4}{Affiliation}#=%=#Qufu Normal University

==========
èéáğö